vignettes/articles/accessing_project_data.Rmd
accessing_project_data.RmdThis article walks through, in detail, accessing data specific to
projects, primarily via mermaid_get_project_data().
To access data related to your MERMAID projects, first obtain a list
of your projects with mermaid_get_my_projects().
At this point, you will have to authenticate to the Collect app. R will help you do this automatically by opening a browser window for you to log in to Collect, either via Google sign-in or username and password - however you normally do!
Once you’ve logged in, come back to R. Your login credentials will be stored for a day, until they expire, and you will need to login again. The package handles the expiration for you, so just log in again when prompted.
library(mermaidr)
my_projects <- mermaid_get_my_projects()
my_projects
#> # A tibble: 16 × 21
#> id name countries num_sites num_active_sample_un…¹ num_sample_units tags
#> <chr> <chr> <chr> <int> <int> <dbl> <chr>
#> 1 e1efb1e0… 2016… Fiji 9 10 80 "WCS…
#> 2 170e7182… 2018… Fiji 10 5 121 "WCS…
#> 3 d065cba4… 2019… Fiji 31 3 32 "WCS…
#> 4 1fbdb9ea… a2 Canada, … 9 9 0 "WWF…
#> 5 3a9ecb7c… Aceh… Indonesia 18 55 198 "WCS…
#> 6 bacd3529… Beli… Belize, … 39 112 258 "WCS…
#> 7 a1b7ff1f… Grea… Fiji 76 8 648 "Fij…
#> 8 507d1af9… Kari… Indonesia 43 18 842 "WCS…
#> 9 75ef7a5a… Kubu… Fiji 78 1 1145 "WCS…
#> 10 5679ef3d… Mada… Madagasc… 33 0 49 "WCS…
#> 11 4080679f… Mada… Madagasc… 74 4 84 "WCS…
#> 12 4d79339f… MERM… Indonesi… 13 72 32 "tes…
#> 13 2c0c9857… Shar… Canada, … 28 5 6 ""
#> 14 02e6915c… TWP … Indonesia 14 10 2 "WCS…
#> 15 2d6cee25… WCS … Mozambiq… 74 6 247 "WCS…
#> 16 9de82789… XPDC… Indonesia 37 71 450 ""
#> # ℹ abbreviated name: ¹num_active_sample_units
#> # ℹ 14 more variables: project_admins <chr>, suggested_citation <chr>,
#> # bbox <df[,4]>, notes <chr>, status <chr>, data_policy_beltfish <chr>,
#> # data_policy_benthiclit <chr>, data_policy_benthicpit <chr>,
#> # data_policy_benthicpqt <chr>, data_policy_habitatcomplexity <chr>,
#> # data_policy_bleachingqc <chr>, data_policy_macroinvertebrate <chr>,
#> # created_on <chr>, updated_on <chr>This function returns information on your projects, including project countries, the number of sites, tags, data policies, and more.
To filter for specific projects, you can use the filter
function from dplyr:
library(dplyr)
indonesia_projects <- my_projects %>%
filter(countries == "Indonesia")
indonesia_projects
#> # A tibble: 4 × 21
#> id name countries num_sites num_active_sample_un…¹ num_sample_units tags
#> <chr> <chr> <chr> <int> <int> <dbl> <chr>
#> 1 3a9ecb7c-… Aceh… Indonesia 18 55 198 "WCS…
#> 2 507d1af9-… Kari… Indonesia 43 18 842 "WCS…
#> 3 02e6915c-… TWP … Indonesia 14 10 2 "WCS…
#> 4 9de82789-… XPDC… Indonesia 37 71 450 ""
#> # ℹ abbreviated name: ¹num_active_sample_units
#> # ℹ 14 more variables: project_admins <chr>, suggested_citation <chr>,
#> # bbox <df[,4]>, notes <chr>, status <chr>, data_policy_beltfish <chr>,
#> # data_policy_benthiclit <chr>, data_policy_benthicpit <chr>,
#> # data_policy_benthicpqt <chr>, data_policy_habitatcomplexity <chr>,
#> # data_policy_bleachingqc <chr>, data_policy_macroinvertebrate <chr>,
#> # created_on <chr>, updated_on <chr>Alternatively, you can search your projects using
mermaid_search_my_projects(), narrowing projects down by
name, countries, or tags:
mermaid_search_my_projects(countries = "Indonesia")
#> # A tibble: 7 × 21
#> id name countries num_sites num_active_sample_un…¹ num_sample_units tags
#> <chr> <chr> <chr> <int> <int> <dbl> <chr>
#> 1 3a9ecb7c-… Aceh… Indonesia 18 55 198 "WCS…
#> 2 bacd3529-… Beli… Belize, … 39 112 258 "WCS…
#> 3 507d1af9-… Kari… Indonesia 43 18 842 "WCS…
#> 4 4d79339f-… MERM… Indonesi… 13 72 32 "tes…
#> 5 2c0c9857-… Shar… Canada, … 28 5 6 ""
#> 6 02e6915c-… TWP … Indonesia 14 10 2 "WCS…
#> 7 9de82789-… XPDC… Indonesia 37 71 450 ""
#> # ℹ abbreviated name: ¹num_active_sample_units
#> # ℹ 14 more variables: project_admins <chr>, suggested_citation <chr>,
#> # bbox <df[,4]>, notes <chr>, status <chr>, data_policy_beltfish <chr>,
#> # data_policy_benthiclit <chr>, data_policy_benthicpit <chr>,
#> # data_policy_benthicpqt <chr>, data_policy_habitatcomplexity <chr>,
#> # data_policy_bleachingqc <chr>, data_policy_macroinvertebrate <chr>,
#> # created_on <chr>, updated_on <chr>Then, you can start to access data about your projects, like project
sites via mermaid_get_project_sites():
indonesia_projects %>%
mermaid_get_project_sites()
#> # A tibble: 112 × 12
#> project id name notes latitude longitude country reef_type reef_zone exposure
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr>
#> 1 Karimu… a763… Gent… "" -5.86 111. Indone… fringing back reef shelter…
#> 2 Aceh J… b7d5… Reha… "" 4.84 95.4 Indone… fringing fore reef shelter…
#> 3 Aceh J… 5436… Wisa… "" 5.04 95.4 Indone… fringing fore reef shelter…
#> 4 Karimu… 0368… Meny… "" -5.80 110. Indone… fringing fore reef shelter…
#> 5 Aceh J… 38f7… Pula… "" 5.08 95.3 Indone… fringing back reef semi-ex…
#> 6 Karimu… 21ae… Batu… "" -5.81 110. Indone… fringing back reef semi-ex…
#> 7 Karimu… f30c… Cema… "" -5.81 110. Indone… fringing back reef semi-ex…
#> 8 Karimu… 9ec6… Cema… "" -5.80 110. Indone… fringing back reef semi-ex…
#> 9 Karimu… 43d3… Lego… "" -5.87 110. Indone… fringing back reef semi-ex…
#> 10 Karimu… f096… Lego… "" -5.86 110. Indone… fringing back reef semi-ex…
#> # ℹ 102 more rows
#> # ℹ 2 more variables: created_on <chr>, updated_on <chr>Or the managements for your projects via
mermaid_get_project_managements():
indonesia_projects %>%
mermaid_get_project_managements()
#> # A tibble: 24 × 18
#> project id name name_secondary est_year size parties compliance open_access
#> <chr> <chr> <chr> <chr> <int> <dbl> <chr> <chr> <lgl>
#> 1 Aceh Ja… cc92… Core… "" 2019 NA commun… full FALSE
#> 2 TWP Gil… 0975… Zona… "Core Zone" 2013 NA govern… full FALSE
#> 3 Aceh Ja… a579… Aqua… "" 2019 NA commun… low FALSE
#> 4 Aceh Ja… 646c… Fish… "" 2019 NA commun… low FALSE
#> 5 Aceh Ja… dce8… Reha… "" 2019 NA commun… low FALSE
#> 6 Aceh Ja… 1498… Tour… "" 2019 NA commun… low FALSE
#> 7 Karimun… 8b90… Fish… "" 2005 0 commun… low FALSE
#> 8 Karimun… bd73… Reha… "" 2005 NA commun… low FALSE
#> 9 Karimun… a7e2… Tour… "" 2005 NA commun… low FALSE
#> 10 Aceh Ja… 0f0f… Open "" 2019 NA commun… none TRUE
#> # ℹ 14 more rows
#> # ℹ 9 more variables: no_take <lgl>, access_restriction <lgl>,
#> # periodic_closure <lgl>, size_limits <lgl>, gear_restriction <lgl>,
#> # species_restriction <lgl>, notes <chr>, created_on <chr>, updated_on <chr>You can also access data on your projects’ Fish Belt, Benthic LIT, Benthic PIT, Macroinvertebrate, Bleaching, and Habitat Complexity methods. The details are in the following sections.
To access Fish Belt data for a project, use
mermaid_get_project_data() with
method = "fishbelt".
You can access individual observations (i.e., a record of each
observation) by setting data = "observations":
xpdc <- my_projects %>%
filter(name == "XPDC Kei Kecil 2018")
xpdc %>%
mermaid_get_project_data(method = "fishbelt", data = "observations")
#> # A tibble: 3,069 × 54
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 2 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 3 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 4 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 5 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 6 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 7 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 8 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 9 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 10 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> # ℹ 3,059 more rows
#> # ℹ 45 more variables: reef_slope <chr>, tide <chr>, current <chr>,
#> # visibility <chr>, relative_depth <chr>, management <chr>,
#> # management_secondary <chr>, management_est_year <lgl>, management_size <lgl>,
#> # management_parties <lgl>, management_compliance <chr>, management_rules <chr>,
#> # sample_date <date>, sample_time <time>, depth <dbl>, transect_length <dbl>,
#> # transect_width <chr>, assigned_transect_width_m <dbl>, size_bin <dbl>, …You can access sample units data, which are observations aggregated to the sample units level. Fish belt sample units contain total biomass in kg/ha per sample unit, by trophic group and by fish family:
xpdc %>%
mermaid_get_project_data("fishbelt", "sampleunits")
#> # A tibble: 246 × 67
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 XPDC Ke… NA Indone… KE34 -5.85 133. fringing crest exposed
#> 2 XPDC Ke… NA Indone… KE06 -5.52 132. fringing crest exposed
#> 3 XPDC Ke… NA Indone… KE23 -5.80 133. fringing fore reef exposed
#> 4 XPDC Ke… NA Indone… KE07 -5.57 133. fringing crest exposed
#> 5 XPDC Ke… NA Indone… KE03 -5.61 132. fringing crest exposed
#> 6 XPDC Ke… NA Indone… KE24 -5.93 133. fringing fore reef exposed
#> 7 XPDC Ke… NA Indone… KE17 -5.69 133. fringing fore reef semi-exposed
#> 8 XPDC Ke… NA Indone… KE31 -5.78 133. fringing crest semi-exposed
#> 9 XPDC Ke… NA Indone… KE36 -5.88 133. fringing fore reef semi-exposed
#> 10 XPDC Ke… NA Indone… KE33 -5.82 133. fringing fore reef semi-exposed
#> # ℹ 236 more rows
#> # ℹ 58 more variables: reef_slope <chr>, tide <chr>, current <chr>,
#> # visibility <chr>, relative_depth <chr>, management <chr>,
#> # management_secondary <chr>, management_est_year <lgl>, management_size <lgl>,
#> # management_parties <lgl>, management_compliance <chr>, management_rules <chr>,
#> # sample_date <date>, sample_time <chr>, depth <dbl>, transect_number <dbl>,
#> # label <lgl>, size_bin <chr>, transect_length <dbl>, transect_width <chr>, …And finally, sample events data, which are aggregated further, to the sample event level. Fish belt sample events contain mean total biomass in kg/ha per sample event, by trophic group and by fish family, as well as standard deviations:
xpdc_sample_events <- xpdc %>%
mermaid_get_project_data("fishbelt", "sampleevents")
xpdc_sample_events
#> # A tibble: 46 × 82
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 XPDC Ke… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 2 XPDC Ke… NA Indone… KE36 -5.88 133. fringing fore reef semi-exposed
#> 3 XPDC Ke… NA Indone… KE36 -5.88 133. fringing fore reef semi-exposed
#> 4 XPDC Ke… NA Indone… KE06 -5.52 132. fringing crest exposed
#> 5 XPDC Ke… NA Indone… KE23 -5.80 133. fringing fore reef exposed
#> 6 XPDC Ke… NA Indone… KE18 -5.70 133. fringing fore reef semi-exposed
#> 7 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 8 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 9 XPDC Ke… NA Indone… KE19 -5.73 133. fringing fore reef semi-exposed
#> 10 XPDC Ke… NA Indone… KE31 -5.78 133. fringing crest semi-exposed
#> # ℹ 36 more rows
#> # ℹ 73 more variables: tide <chr>, current <chr>, visibility <chr>,
#> # management <chr>, management_secondary <chr>, management_est_year <lgl>,
#> # management_size <lgl>, management_parties <lgl>, management_compliance <chr>,
#> # management_rules <chr>, sample_date <date>, depth_avg <dbl>, depth_sd <dbl>,
#> # biomass_kgha_avg <dbl>, biomass_kgha_sd <dbl>,
#> # biomass_kgha_trophic_group_avg_omnivore <dbl>, …To access Benthic LIT data, use
mermaid_get_project_data() with
method = "benthiclit".
mozambique <- my_projects %>%
filter(name == "WCS Mozambique Coral Reef Monitoring")
mozambique %>%
mermaid_get_project_data(method = "benthiclit", data = "observations")
#> # A tibble: 1,574 × 47
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 WCS Moz… WCS … Mozamb… Ligh… -11.0 40.7 fringing crest exposed
#> 2 WCS Moz… WCS … Mozamb… Ligh… -11.0 40.7 fringing crest exposed
#> 3 WCS Moz… WCS … Mozamb… Ligh… -11.0 40.7 fringing crest exposed
#> 4 WCS Moz… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 5 WCS Moz… WCS … Mozamb… Ligh… -11.0 40.7 fringing crest exposed
#> 6 WCS Moz… WCS … Mozamb… Ligh… -11.0 40.7 fringing crest exposed
#> 7 WCS Moz… WCS … Mozamb… Ligh… -11.0 40.7 fringing crest exposed
#> 8 WCS Moz… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 9 WCS Moz… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 10 WCS Moz… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> # ℹ 1,564 more rows
#> # ℹ 38 more variables: reef_slope <lgl>, tide <chr>, current <lgl>,
#> # visibility <lgl>, relative_depth <lgl>, management <chr>,
#> # management_secondary <lgl>, management_est_year <dbl>, management_size <lgl>,
#> # management_parties <chr>, management_compliance <chr>, management_rules <chr>,
#> # sample_date <date>, sample_time <time>, depth <dbl>, transect_number <dbl>,
#> # transect_length <dbl>, label <lgl>, observers <chr>, benthic_category <chr>, …You can access sample units and sample events the same way.
For Benthic LIT, sample units contain percent cover per sample unit, by benthic category.
mozambique %>%
mermaid_get_project_data(method = "benthiclit", data = "sampleunits")
#> # A tibble: 64 × 56
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 WCS Moz… WCS … Mozamb… Pang… -11.0 40.6 lagoon back reef semi-exposed
#> 2 WCS Moz… WCS … Mozamb… Barr… -26.1 32.9 barrier back reef sheltered
#> 3 WCS Moz… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 4 WCS Moz… WCS … Mozamb… Lond… -12.9 40.5 fringing fore reef exposed
#> 5 WCS Moz… WCS … Mozamb… Ligh… -11.0 40.7 fringing crest exposed
#> 6 WCS Moz… WCS … Mozamb… Pang… -11.0 40.6 lagoon back reef semi-exposed
#> 7 WCS Moz… WCS … Mozamb… Lond… -12.9 40.5 fringing back reef sheltered
#> 8 WCS Moz… WCS … Mozamb… Pemb… -13.0 40.6 fringing back reef exposed
#> 9 WCS Moz… WCS … Mozamb… Lond… -12.9 40.5 fringing fore reef exposed
#> 10 WCS Moz… WCS … Mozamb… Pont… -26.1 33.0 barrier crest sheltered
#> # ℹ 54 more rows
#> # ℹ 47 more variables: reef_slope <lgl>, tide <chr>, current <lgl>,
#> # visibility <lgl>, relative_depth <lgl>, management <chr>,
#> # management_secondary <lgl>, management_est_year <dbl>, management_size <lgl>,
#> # management_parties <chr>, management_compliance <chr>, management_rules <chr>,
#> # sample_date <date>, sample_time <time>, depth <dbl>, transect_number <dbl>,
#> # transect_length <dbl>, label <lgl>, observers <chr>, …Sample events contain mean percent cover per sample event, by benthic category, and standard deviations for these values:
mozambique %>%
mermaid_get_project_data(method = "benthiclit", data = "sampleevents")
#> # A tibble: 12 × 66
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 WCS Moz… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered
#> 2 WCS Moz… WCS … Mozamb… Pang… -11.0 40.6 lagoon back reef semi-exposed
#> 3 WCS Moz… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 4 WCS Moz… WCS … Mozamb… Pemb… -13.0 40.6 fringing back reef exposed
#> 5 WCS Moz… WCS … Mozamb… Ligh… -11.0 40.7 fringing crest exposed
#> 6 WCS Moz… WCS … Mozamb… Lond… -12.9 40.5 fringing back reef sheltered
#> 7 WCS Moz… WCS … Mozamb… Pont… -26.1 33.0 barrier crest sheltered
#> 8 WCS Moz… WCS … Mozamb… Lond… -12.9 40.5 fringing fore reef exposed
#> 9 WCS Moz… WCS … Mozamb… Lond… -12.9 40.5 fringing fore reef exposed
#> 10 WCS Moz… WCS … Mozamb… Pang… -11.0 40.6 lagoon back reef semi-exposed
#> 11 WCS Moz… WCS … Mozamb… Barr… -26.1 32.9 barrier back reef sheltered
#> 12 WCS Moz… WCS … Mozamb… Bunt… -12.6 40.6 fringing fore reef exposed
#> # ℹ 57 more variables: tide <chr>, current <lgl>, visibility <lgl>,
#> # management <chr>, management_secondary <lgl>, management_est_year <dbl>,
#> # management_size <lgl>, management_parties <chr>, management_compliance <chr>,
#> # management_rules <chr>, sample_date <date>, depth_avg <dbl>, depth_sd <dbl>,
#> # percent_cover_benthic_category_avg_sand <dbl>,
#> # percent_cover_benthic_category_avg_trash <dbl>,
#> # percent_cover_benthic_category_avg_rubble <dbl>, …To access Benthic PIT data, change method to
“benthicpit”:
xpdc %>%
mermaid_get_project_data(method = "benthicpit", data = "observations")
#> # A tibble: 11,100 × 48
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 2 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 3 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 4 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 5 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 6 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 7 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 8 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 9 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 10 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> # ℹ 11,090 more rows
#> # ℹ 39 more variables: reef_slope <chr>, tide <chr>, current <chr>,
#> # visibility <chr>, relative_depth <chr>, management <chr>,
#> # management_secondary <chr>, management_est_year <lgl>, management_size <lgl>,
#> # management_parties <lgl>, management_compliance <chr>, management_rules <chr>,
#> # sample_date <date>, sample_time <time>, depth <dbl>, transect_number <dbl>,
#> # transect_length <dbl>, label <lgl>, observers <chr>, benthic_category <chr>, …You can access sample units and sample events the same way, and the data format is the same as Benthic LIT.
You can return both sample units and sample events by setting the
data argument. This will return a list of two data frames:
one containing sample units, and the other sample events.
xpdc_sample_units_events <- xpdc %>%
mermaid_get_project_data(method = "benthicpit", data = c("sampleunits", "sampleevents"))
names(xpdc_sample_units_events)
#> [1] "sampleunits" "sampleevents"
xpdc_sample_units_events[["sampleunits"]]
#> # A tibble: 111 × 57
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 XPDC Ke… NA Indone… KE32 -5.79 133. fringing fore reef semi-exposed
#> 2 XPDC Ke… NA Indone… KE07 -5.57 133. fringing crest exposed
#> 3 XPDC Ke… NA Indone… KE14 -5.51 133. patch crest exposed
#> 4 XPDC Ke… NA Indone… KE26 -5.70 133. fringing crest exposed
#> 5 XPDC Ke… NA Indone… KE19 -5.73 133. fringing fore reef semi-exposed
#> 6 XPDC Ke… NA Indone… KE36 -5.88 133. fringing fore reef semi-exposed
#> 7 XPDC Ke… NA Indone… KE26 -5.70 133. fringing crest exposed
#> 8 XPDC Ke… NA Indone… KE09 -5.60 133. fringing fore reef semi-exposed
#> 9 XPDC Ke… NA Indone… KE17 -5.69 133. fringing fore reef semi-exposed
#> 10 XPDC Ke… NA Indone… KE06 -5.52 132. fringing crest exposed
#> # ℹ 101 more rows
#> # ℹ 48 more variables: reef_slope <chr>, tide <chr>, current <chr>,
#> # visibility <chr>, relative_depth <chr>, management <chr>,
#> # management_secondary <chr>, management_est_year <lgl>, management_size <lgl>,
#> # management_parties <lgl>, management_compliance <chr>, management_rules <chr>,
#> # sample_date <date>, sample_time <time>, depth <dbl>, transect_number <dbl>,
#> # transect_length <dbl>, label <lgl>, observers <chr>, …To access Benthic PQT data, change method to
“benthicpqt”:
glovers_atoll <- my_projects %>%
filter(name == "Belize Glover's Atoll 2020")
glovers_atoll %>%
mermaid_get_project_data(method = "benthicpqt", data = "observations")
#> # A tibble: 14 × 45
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 Belize … WCS … Camero… test 44.1 -90.8 barrier crest sheltered
#> 2 Belize … WCS … Camero… test 44.1 -90.8 barrier crest sheltered
#> 3 Belize … WCS … Camero… test 44.1 -90.8 barrier crest sheltered
#> 4 Belize … WCS … Camero… test 44.1 -90.8 barrier crest sheltered
#> 5 Belize … WCS … Camero… test 44.1 -90.8 barrier crest sheltered
#> 6 Belize … WCS … Camero… test 44.1 -90.8 barrier crest sheltered
#> 7 Belize … WCS … Camero… test 44.1 -90.8 barrier crest sheltered
#> 8 Belize … WCS … Camero… test 44.1 -90.8 barrier crest sheltered
#> 9 Belize … WCS … Camero… test 44.1 -90.8 barrier crest sheltered
#> 10 Belize … WCS … Camero… test 44.1 -90.8 barrier crest sheltered
#> 11 Belize … WCS … Camero… test 44.1 -90.8 barrier crest sheltered
#> 12 Belize … WCS … Belize CZFR1 16.7 -87.8 atoll fore reef exposed
#> 13 Belize … WCS … Belize CZFR1 16.7 -87.8 atoll fore reef exposed
#> 14 Belize … WCS … Belize CZFR1 16.7 -87.8 atoll fore reef exposed
#> # ℹ 36 more variables: reef_slope <chr>, tide <chr>, current <chr>,
#> # visibility <chr>, relative_depth <chr>, management <chr>,
#> # management_secondary <lgl>, management_est_year <lgl>, management_size <lgl>,
#> # management_parties <chr>, management_compliance <chr>, management_rules <chr>,
#> # sample_date <date>, sample_time <lgl>, depth <dbl>, transect_number <dbl>,
#> # transect_length <dbl>, label <dbl>, observers <chr>, benthic_category <chr>, …You can access sample units and sample events the same way.
Sample units contains percent cover per sample unit, by benthic category and by life histories.
glovers_atoll %>%
mermaid_get_project_data(method = "benthicpqt", data = "sampleunits")
#> # A tibble: 2 × 55
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 Belize G… WCS … Belize CZFR1 16.7 -87.8 atoll fore reef exposed
#> 2 Belize G… WCS … Camero… test 44.1 -90.8 barrier crest sheltered
#> # ℹ 46 more variables: reef_slope <chr>, tide <chr>, current <chr>,
#> # visibility <chr>, relative_depth <chr>, management <chr>,
#> # management_secondary <lgl>, management_est_year <lgl>, management_size <lgl>,
#> # management_parties <chr>, management_compliance <chr>, management_rules <chr>,
#> # sample_date <date>, sample_time <lgl>, depth <dbl>, transect_number <dbl>,
#> # transect_length <dbl>, label <dbl>, observers <chr>,
#> # percent_cover_benthic_category_sand <dbl>, …Sample events contains mean percent cover per sample event, by benthic category and by life histories, and standard deviations for these values:
glovers_atoll %>%
mermaid_get_project_data(method = "benthicpqt", data = "sampleevents")
#> # A tibble: 2 × 66
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 Belize G… WCS … Camero… test 44.1 -90.8 barrier crest sheltered
#> 2 Belize G… WCS … Belize CZFR1 16.7 -87.8 atoll fore reef exposed
#> # ℹ 57 more variables: tide <chr>, current <chr>, visibility <chr>,
#> # management <chr>, management_secondary <lgl>, management_est_year <lgl>,
#> # management_size <lgl>, management_parties <chr>, management_compliance <chr>,
#> # management_rules <chr>, sample_date <date>, depth_avg <dbl>, depth_sd <lgl>,
#> # percent_cover_benthic_category_avg_sand <dbl>,
#> # percent_cover_benthic_category_avg_trash <dbl>,
#> # percent_cover_benthic_category_avg_rubble <dbl>, …To access Macroinvertebrate data, set method to
“macroinvertebrate”.
Observations data includes size, count, and density, with a full breakdown of macroinvertebrate class, order, family, genus, and group of interest, along with the size, count, and density.
glovers_atoll %>%
mermaid_get_project_data(method = "macroinvertebrate", data = "observations")
#> # A tibble: 55 × 49
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr> <chr> <chr>
#> 1 Belize … WCS … Indone… 1207 -3.16 135. fringing back reef sheltered
#> 2 Belize … WCS … Indone… 1207 -3.16 135. fringing back reef sheltered
#> 3 Belize … WCS … Indone… 1207 -3.16 135. fringing back reef sheltered
#> 4 Belize … WCS … Indone… 1207 -3.16 135. fringing back reef sheltered
#> 5 Belize … WCS … Indone… 1207 -3.16 135. fringing back reef sheltered
#> 6 Belize … WCS … Indone… 1201 2 44 fringing fore reef exposed
#> 7 Belize … WCS … Indone… 1201 2 44 fringing fore reef exposed
#> 8 Belize … WCS … Indone… 1201 2 44 fringing fore reef exposed
#> 9 Belize … WCS … Indone… 1201 2 44 fringing fore reef exposed
#> 10 Belize … WCS … Indone… 1201 2 44 fringing fore reef exposed
#> # ℹ 45 more rows
#> # ℹ 40 more variables: tide <lgl>, current <lgl>, visibility <lgl>,
#> # relative_depth <lgl>, management <chr>, management_secondary <lgl>,
#> # management_est_year <lgl>, management_size <dbl>, management_parties <chr>,
#> # management_compliance <chr>, management_rules <chr>, sample_date <date>,
#> # sample_time <time>, depth <dbl>, transect_length <dbl>, transect_width <chr>,
#> # observers <chr>, transect_number <dbl>, label <lgl>, size_bin <dbl>, …Sample units data returns total abundance and density, as well as density by group of interest, and sample events contain density per sample event, by group of interest, and standard deviations of these values.
glovers_atoll %>%
mermaid_get_project_data(method = "macroinvertebrate", data = "sampleunits")
#> # A tibble: 10 × 56
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr> <chr> <chr>
#> 1 Belize … WCS … Indone… 1201 2 44 fringing fore reef exposed
#> 2 Belize … WCS … Indone… 1201 2 44 fringing fore reef exposed
#> 3 Belize … WCS … Indone… 1201 2 44 fringing fore reef exposed
#> 4 Belize … WCS … Indone… 1207 -3.16 135. fringing back reef sheltered
#> 5 Belize … WCS … Indone… 1201 2 44 fringing fore reef exposed
#> 6 Belize … WCS … Indone… 1207 -3.16 135. fringing back reef sheltered
#> 7 Belize … WCS … Indone… 1207 -3.16 135. fringing back reef sheltered
#> 8 Belize … WCS … Indone… 1207 -3.16 135. fringing back reef sheltered
#> 9 Belize … WCS … Indone… 1201 2 44 fringing fore reef exposed
#> 10 Belize … WCS … Indone… 1207 -3.16 135. fringing back reef sheltered
#> # ℹ 47 more variables: tide <lgl>, current <lgl>, visibility <lgl>,
#> # relative_depth <lgl>, management <chr>, management_secondary <lgl>,
#> # management_est_year <lgl>, management_size <dbl>, management_parties <chr>,
#> # management_compliance <chr>, management_rules <chr>, sample_date <date>,
#> # sample_time <time>, depth <dbl>, transect_number <dbl>, label <lgl>,
#> # size_bin <dbl>, transect_length <dbl>, transect_width <chr>,
#> # total_abundance <dbl>, …To access Bleaching data, set method to “bleaching”.
There are two types of observations data for the Bleaching method:
Colonies Bleached and Percent Cover. These are both returned when
pulling observations data, in a list:
bleaching_obs <- mozambique %>%
mermaid_get_project_data("bleaching", "observations")
names(bleaching_obs)
#> [1] "colonies_bleached" "percent_cover"
bleaching_obs[["colonies_bleached"]]
#> # A tibble: 1,814 × 50
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 WCS Moz… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered
#> 2 WCS Moz… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered
#> 3 WCS Moz… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered
#> 4 WCS Moz… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered
#> 5 WCS Moz… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered
#> 6 WCS Moz… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered
#> 7 WCS Moz… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered
#> 8 WCS Moz… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered
#> 9 WCS Moz… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered
#> 10 WCS Moz… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered
#> # ℹ 1,804 more rows
#> # ℹ 41 more variables: tide <lgl>, current <lgl>, visibility <lgl>,
#> # relative_depth <lgl>, management <chr>, management_secondary <lgl>,
#> # management_est_year <dbl>, management_size <lgl>, management_parties <chr>,
#> # management_compliance <chr>, management_rules <chr>, sample_date <date>,
#> # sample_time <time>, depth <dbl>, quadrat_size <dbl>, label <chr>,
#> # observers <chr>, benthic_attribute <chr>, benthic_category <chr>, …The sample units and sample events data contain summaries of both Colonies Bleached and Percent Cover:
mozambique %>%
mermaid_get_project_data("bleaching", "sampleevents")
#> # A tibble: 62 × 70
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 WCS Moz… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered
#> 2 WCS Moz… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered
#> 3 WCS Moz… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered
#> 4 WCS Moz… WCS … Mozamb… Pang… -11.0 40.6 barrier crest semi-exposed
#> 5 WCS Moz… WCS … Mozamb… Two … -21.8 35.5 barrier fore reef exposed
#> 6 WCS Moz… WCS … Mozamb… Luta… -12.3 40.6 fringing fore reef exposed
#> 7 WCS Moz… WCS … Mozamb… Pang… -11.0 40.6 lagoon back reef semi-exposed
#> 8 WCS Moz… WCS … Mozamb… Baby… -11.0 40.7 fringing fore reef exposed
#> 9 WCS Moz… WCS … Mozamb… Zala… -12.0 40.6 lagoon back reef exposed
#> 10 WCS Moz… WCS … Mozamb… Pemb… -13.0 40.6 fringing fore reef exposed
#> # ℹ 52 more rows
#> # ℹ 61 more variables: tide <lgl>, current <lgl>, visibility <lgl>,
#> # management <chr>, management_secondary <lgl>, management_est_year <dbl>,
#> # management_size <lgl>, management_parties <chr>, management_compliance <chr>,
#> # management_rules <chr>, sample_date <date>, depth_avg <dbl>, depth_sd <dbl>,
#> # quadrat_size_avg <dbl>, count_total_avg <dbl>, count_total_sd <dbl>,
#> # count_genera_avg <dbl>, count_genera_sd <dbl>, percent_normal_avg <dbl>, …Finally, to access Habitat Complexity data, set method
to “habitatcomplexity”. As with all other methods, you can access
observations, sample units, and sample events:
xpdc %>%
mermaid_get_project_data("habitatcomplexity", "sampleevents")
#> # A tibble: 2 × 36
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 XPDC Kei… NA Indone… KE22 -5.85 133. fringing fore reef exposed
#> 2 XPDC Kei… NA Indone… KE24 -5.93 133. fringing fore reef exposed
#> # ℹ 27 more variables: tide <chr>, current <chr>, visibility <chr>,
#> # management <chr>, management_secondary <chr>, management_est_year <lgl>,
#> # management_size <lgl>, management_parties <lgl>, management_compliance <lgl>,
#> # management_rules <chr>, sample_date <date>, depth_avg <dbl>, depth_sd <dbl>,
#> # score_avg_avg <dbl>, score_avg_sd <dbl>, data_policy_habitatcomplexity <chr>,
#> # observers <chr>, project_notes <chr>, site_notes <lgl>, management_notes <lgl>,
#> # …To pull data for both fish belt and benthic PIT methods, you can set
method to include both.
xpdc_sample_events <- xpdc %>%
mermaid_get_project_data(method = c("fishbelt", "benthicpit"), data = "sampleevents")The result is a list of data frames, containing sample events for both fish belt and benthic PIT methods:
names(xpdc_sample_events)
#> [1] "fishbelt" "benthicpit"
xpdc_sample_events[["benthicpit"]]
#> # A tibble: 38 × 66
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 XPDC Ke… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 2 XPDC Ke… NA Indone… KE36 -5.88 133. fringing fore reef semi-exposed
#> 3 XPDC Ke… NA Indone… KE06 -5.52 132. fringing crest exposed
#> 4 XPDC Ke… NA Indone… KE23 -5.80 133. fringing fore reef exposed
#> 5 XPDC Ke… NA Indone… KE18 -5.70 133. fringing fore reef semi-exposed
#> 6 XPDC Ke… NA Indone… KE13 -5.51 133. patch crest exposed
#> 7 XPDC Ke… NA Indone… KE19 -5.73 133. fringing fore reef semi-exposed
#> 8 XPDC Ke… NA Indone… KE31 -5.78 133. fringing crest semi-exposed
#> 9 XPDC Ke… NA Indone… KE20 -5.67 133. fringing fore reef semi-exposed
#> 10 XPDC Ke… NA Indone… KE40 -6.00 132. fringing fore reef exposed
#> # ℹ 28 more rows
#> # ℹ 57 more variables: tide <chr>, current <chr>, visibility <chr>,
#> # management <chr>, management_secondary <chr>, management_est_year <lgl>,
#> # management_size <lgl>, management_parties <lgl>, management_compliance <chr>,
#> # management_rules <chr>, sample_date <date>, depth_avg <dbl>, depth_sd <dbl>,
#> # percent_cover_benthic_category_avg_sand <dbl>,
#> # percent_cover_benthic_category_avg_trash <dbl>, …Alternatively, you can set method to “all” to pull for
all methods! Similarly, you can set data to “all” to pull
all types of data:
all_project_data <- xpdc %>%
mermaid_get_project_data(method = "all", data = "all", limit = 1)
names(all_project_data)
#> [1] "fishbelt" "benthicpit" "benthicpqt" "benthiclit"
#> [5] "habitatcomplexity" "bleaching" "macroinvertebrate"
names(all_project_data[["benthicpit"]])
#> [1] "observations" "sampleunits" "sampleevents"Pulling data for multiple projects is the exact same, except there will be an additional “project” column at the beginning to distinguish which projects the data comes from.
my_projects
#> # A tibble: 16 × 21
#> id name countries num_sites num_active_sample_un…¹ num_sample_units tags
#> <chr> <chr> <chr> <int> <int> <dbl> <chr>
#> 1 e1efb1e0… 2016… Fiji 9 10 80 "WCS…
#> 2 170e7182… 2018… Fiji 10 5 121 "WCS…
#> 3 d065cba4… 2019… Fiji 31 3 32 "WCS…
#> 4 1fbdb9ea… a2 Canada, … 9 9 0 "WWF…
#> 5 3a9ecb7c… Aceh… Indonesia 18 55 198 "WCS…
#> 6 bacd3529… Beli… Belize, … 39 112 258 "WCS…
#> 7 a1b7ff1f… Grea… Fiji 76 8 648 "Fij…
#> 8 507d1af9… Kari… Indonesia 43 18 842 "WCS…
#> 9 75ef7a5a… Kubu… Fiji 78 1 1145 "WCS…
#> 10 5679ef3d… Mada… Madagasc… 33 0 49 "WCS…
#> 11 4080679f… Mada… Madagasc… 74 4 84 "WCS…
#> 12 4d79339f… MERM… Indonesi… 13 72 32 "tes…
#> 13 2c0c9857… Shar… Canada, … 28 5 6 ""
#> 14 02e6915c… TWP … Indonesia 14 10 2 "WCS…
#> 15 2d6cee25… WCS … Mozambiq… 74 6 247 "WCS…
#> 16 9de82789… XPDC… Indonesia 37 71 450 ""
#> # ℹ abbreviated name: ¹num_active_sample_units
#> # ℹ 14 more variables: project_admins <chr>, suggested_citation <chr>,
#> # bbox <df[,4]>, notes <chr>, status <chr>, data_policy_beltfish <chr>,
#> # data_policy_benthiclit <chr>, data_policy_benthicpit <chr>,
#> # data_policy_benthicpqt <chr>, data_policy_habitatcomplexity <chr>,
#> # data_policy_bleachingqc <chr>, data_policy_macroinvertebrate <chr>,
#> # created_on <chr>, updated_on <chr>
my_projects %>%
head(5) %>%
mermaid_get_project_data("fishbelt", "sampleevents", limit = 1)
#> # A tibble: 3 × 138
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 2016_Nam… WCS … Fiji C3 -17.1 179. barrier fore reef exposed
#> 2 2018_Vat… WCS … Fiji VIR1 -17.3 178. barrier fore reef exposed
#> 3 Aceh Jay… Vibr… Indone… Pula… 4.78 95.4 fringing fore reef semi-exposed
#> # ℹ 129 more variables: tide <chr>, current <chr>, visibility <chr>,
#> # management <chr>, management_secondary <lgl>, management_est_year <dbl>,
#> # management_size <lgl>, management_parties <chr>, management_compliance <chr>,
#> # management_rules <chr>, sample_date <date>, depth_avg <dbl>, depth_sd <dbl>,
#> # biomass_kgha_avg <dbl>, biomass_kgha_sd <dbl>,
#> # biomass_kgha_trophic_group_avg_omnivore <dbl>,
#> # biomass_kgha_trophic_group_avg_piscivore <dbl>, …Note the limit argument here, which just limits the data
pulled to one record (per project, method, and data combination). This
is useful if you want to get a preview of what your data will look like
without having to pull it all in.
Prior to mermaidr 0.7.0, covariates were automatically
included in all mermaid_get_project_data() function calls.
Now, to access covariates, include covariates = TRUE in the
function call:
my_projects %>%
head(1) %>%
mermaid_get_project_data("fishbelt", "sampleevents", limit = 1, covariates = TRUE)
#> # A tibble: 1 × 102
#> site_id project tags country site latitude longitude reef_type reef_zone
#> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr>
#> 1 05323592-23b6-… 2016_N… WCS … Fiji C3 -17.1 179. barrier fore reef
#> # ℹ 93 more variables: reef_exposure <chr>, tide <lgl>, current <lgl>,
#> # visibility <lgl>, aca_geomorphic <chr>, aca_benthic <chr>,
#> # andrello_grav_nc <dbl>, andrello_sediment <dbl>, andrello_nutrient <dbl>,
#> # andrello_pop_count <dbl>, andrello_num_ports <dbl>, andrello_reef_value <dbl>,
#> # andrello_cumul_score <dbl>, beyer_score <dbl>, beyer_scorecn <dbl>,
#> # beyer_scorecy <dbl>, beyer_scorepfc <dbl>, beyer_scoreth <dbl>,
#> # beyer_scoretr <dbl>, management <chr>, …You can also access covariates at the site level, using
mermaid_get_project_sites() with
covariates = TRUE:
my_projects %>%
mermaid_get_project_sites(covariates = TRUE)
#> # A tibble: 586 × 27
#> project id name notes latitude longitude country reef_type reef_zone exposure
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr>
#> 1 Sharla… 547d… bulk… "" 47.5 -81.8 Canada atoll back reef very sh…
#> 2 Great … 9c2f… BA02 "Sou… -17.4 178. Fiji atoll back reef very sh…
#> 3 Great … c8bd… BA03 "" -17.4 178. Fiji atoll back reef very sh…
#> 4 Great … aa47… BA04 "" -17.4 178. Fiji atoll back reef very sh…
#> 5 Great … 87ab… BA05 "" -17.4 178. Fiji atoll back reef very sh…
#> 6 Great … dbd9… BA06 "" -17.4 178. Fiji atoll back reef very sh…
#> 7 Great … a684… BA07 "" -17.5 178. Fiji atoll back reef very sh…
#> 8 Great … 5cc3… BA08 "" -17.4 178. Fiji atoll back reef very sh…
#> 9 Great … 0235… BA09 "" -17.4 178. Fiji atoll back reef very sh…
#> 10 Great … 2f08… BA10 "" -17.3 178. Fiji atoll back reef very sh…
#> # ℹ 576 more rows
#> # ℹ 17 more variables: aca_geomorphic <chr>, aca_benthic <chr>,
#> # andrello_grav_nc <dbl>, andrello_sediment <dbl>, andrello_nutrient <dbl>,
#> # andrello_pop_count <dbl>, andrello_num_ports <dbl>, andrello_reef_value <dbl>,
#> # andrello_cumul_score <dbl>, beyer_score <dbl>, beyer_scorecn <dbl>,
#> # beyer_scorecy <dbl>, beyer_scorepfc <dbl>, beyer_scoreth <dbl>,
#> # beyer_scoretr <dbl>, created_on <chr>, updated_on <chr>